Is AI Feedback Helping Students or Just Their Papers?

In this episode we explore what happens when AI writing feedback improves a paper without necessarily improving the writer. Using new research from the University of Pennsylvania on graduate students using an AI teaching assistant, we look at the difference between revision and real learning, why group feedback can mask individual understanding, and what teachers can do to make AI feedback more instructionally meaningful.Topics covered:How AI feedback can lead to revision without deep learningWhat a University of Pennsylvania study reveals about student writing improvementWhy group work can hide whether individual students actually learnedThe difference between fixing writing and understanding writingWhy structured reflection should be part of any AI feedback workflowHow teachers can help students process feedback more thoughtfullyWhat district leaders should look for in AI writing-feedback toolsThe risk of overwhelming students with too much unprioritized feedbackWhy revision is evidence of compliance, not always evidence of understandingSource:https://learninganalytics.upenn.edu/ryanbaker/20_U%20Penn%20team%20-%20Do%20Students%20Learn%20from%20Writing%20Feedback%20from%20an%20AI%20Teaching%20Assistant.pdf